The Five Minute Interview – V2i

This article is one in a series of quick-hit interviews with companies using Apache Cassandra and/or DataStax Enterprise for key parts of their business. For this interview, we chatted with V2i’s Philippe Modard who is an engineer and CTO of the company’s applied sciences health monitoring solution.

DataStax: Philippe, we appreciate you carving out time to talk today. Give us the scoop on what you guys do at V2i.

Philippe: V2i is a design and experimental testing company specializing in the field of structural dynamics. The company develops, uses and markets solutions for improving the design, mechanic strength and life of equipment and structures. V2i also offers a wide range of facilities and services for monitoring of production equipment.

DataStax: Tell us a little about your monitoring application and how it uses Cassandra.

Philippe: We install our monitoring software (written in NodeJS) that’s designed to monitor physical structures at customer sites, and that then feeds all the statistical data about a particular structure – that is time series in nature – into our Cassandra database cluster. Our Cassandra database resides in the cloud on Amazon, so the offering is one that is cloud-based.

DataStax: What caused you to pick Cassandra over other options?

Philippe: I had used MongoDB for some previous applications, but it was clear that it wasn’t the right choice for this system. As you can probably tell, this is a very write intensive application, plus it uses time series data, and this steered us away from MongoDB.

Other factors that came into play included:

Cassandra’s performance over other competitors

Its linear scale capabilities (as we don’t know how many systems will ultimately plug into our cloud solution, we have to be ready to quickly scale and still perform the same)

There being no single point of failure; it just keeps running

The tunable data consistency feature was very attractive

DataStax: How easy/hard did you find Cassandra to use?

Philippe: The big difference over relational databases is the data model. Once we understood how things needed to be modeled and defined, everything else was a piece of cake.